Title :
Structure analysis of Chinese Peking Opera
Author :
Ziqiang Zhang ; Xinwei Wang
Author_Institution :
Dept. of Comput. Sci., East China Normal Univ., Shanghai, China
Abstract :
Automatic processing of Chinese Peking Opera becomes more important than ever before. This paper presents a multistage system for structure analysis of Chinese Peking Opera. Taking advantage of opera theory, all procedures fits human´s usual practice appropriately. Especially, a clustering technique is employed for collecting all concrete timbre types. The bottom-top strategy is also presented to reconstruct the structure which discriminates components of Peking Opera. Firstly timbre information sequence is obtained using Viterbi algorithm. There will be coherences or abrupt changes in this sequence generally. Then we gather component information of opera via Forward algorithm in a series of well-trained HMM. Finally, another Viterbi algorithm revised by greedy theory is applied to eliminate petty slices that smoothes the sequence and gets rid of possible errors. The proposed system has been tested on various Peking Opera recordings. These results are shown to demonstrate the performance of this system.
Keywords :
audio signal processing; greedy algorithms; hidden Markov models; information retrieval; maximum likelihood estimation; music; pattern clustering; Chinese Peking Opera; Viterbi algorithm; clustering technique; forward algorithm; greedy theory; hidden Markov model; information retrieval; multistage system; structure analysis; timbre information sequence; well-trained HMM; Feature extraction; Hidden Markov models; Mel frequency cepstral coefficient; Probability distribution; Timbre; Viterbi algorithm; HMM; Hierarchical; Peking Opera; Structure Analysis; Viterbi;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022090